区间形DP - Backyard of LixinZhang



区间形DP - Backyard of LixinZhang

区间形DP特征:

F[i][j]=F[i][k]+F[k+1][j]+CostFunction(i,j)

石子合并

题目描述

有n堆石子排成一列,每堆石子有一个重量w[i], 每次合并可以合并相邻的两堆石子,一次合并的代价为两堆石子的重量和w[i]+w[i+1]。问安排怎样的合并顺序,能够使得总合并代价达到最小。

分析

设状态为F[i][j],表示第i堆到第j堆石子合并之后的最小分值,那么其上一状态一定是由两个子堆合并而来,那么枚举中间分割位置k为决策状态,因此状态转移方程:

F[i][j]=F[i][k]+F[k+1][j]+sum(i,j)
其中sum(i,j)为两个自堆合并时,所产生的分值。

此类DP,先计算小区间,然后再通过小区间迭代得到大区间的值。

同类型的一道面试题

说有n个节点n条边组成一个圈,每个节点上面有一个数,边上有一个+或*,如果消掉某条边,其相邻两个节点就用这个运算符合并。这样一路消边到底,问用什么过程能让最后得到的数最大。


Read full article from 区间形DP - Backyard of LixinZhang


No comments:

Post a Comment

Labels

Algorithm (219) Lucene (130) LeetCode (97) Database (36) Data Structure (33) text mining (28) Solr (27) java (27) Mathematical Algorithm (26) Difficult Algorithm (25) Logic Thinking (23) Puzzles (23) Bit Algorithms (22) Math (21) List (20) Dynamic Programming (19) Linux (19) Tree (18) Machine Learning (15) EPI (11) Queue (11) Smart Algorithm (11) Operating System (9) Java Basic (8) Recursive Algorithm (8) Stack (8) Eclipse (7) Scala (7) Tika (7) J2EE (6) Monitoring (6) Trie (6) Concurrency (5) Geometry Algorithm (5) Greedy Algorithm (5) Mahout (5) MySQL (5) xpost (5) C (4) Interview (4) Vi (4) regular expression (4) to-do (4) C++ (3) Chrome (3) Divide and Conquer (3) Graph Algorithm (3) Permutation (3) Powershell (3) Random (3) Segment Tree (3) UIMA (3) Union-Find (3) Video (3) Virtualization (3) Windows (3) XML (3) Advanced Data Structure (2) Android (2) Bash (2) Classic Algorithm (2) Debugging (2) Design Pattern (2) Google (2) Hadoop (2) Java Collections (2) Markov Chains (2) Probabilities (2) Shell (2) Site (2) Web Development (2) Workplace (2) angularjs (2) .Net (1) Amazon Interview (1) Android Studio (1) Array (1) Boilerpipe (1) Book Notes (1) ChromeOS (1) Chromebook (1) Codility (1) Desgin (1) Design (1) Divide and Conqure (1) GAE (1) Google Interview (1) Great Stuff (1) Hash (1) High Tech Companies (1) Improving (1) LifeTips (1) Maven (1) Network (1) Performance (1) Programming (1) Resources (1) Sampling (1) Sed (1) Smart Thinking (1) Sort (1) Spark (1) Stanford NLP (1) System Design (1) Trove (1) VIP (1) tools (1)

Popular Posts